​The project – which involves large-scale noise monitoring – leverages the latest in machine learning technology, big data analysis, and citizen science reporting to more effectively monitor, analyze, and mitigate urban noise pollution. Known as Sounds of New York City (SONYC), this multi-year project has received a $4.6 million grant from the National Science Foundation and has the support of City health and environmental agencies.

Further information about the project project can be found on the SONYC website. You can also check out the SONYC intro video:

Collecting reliable, real-time data on the migratory patterns of birds can help foster more effective conservation practices, and – when correlated with other data – provide insight into important environmental phenomena. Scientists at CLO currently rely on information from weather surveillance radar, as well as reporting data from over 400,000 active birdwatchers, one of the largest and longest-standing citizen science networks in existence. However, there are important gaps in this information since radar imaging cannot differentiate between species, and most birds migrate at night, unobserved by citizen scientists. The combination of acoustic sensing and machine listening in this project addresses these shortcomings, providing valuable species-specific data that can help biologists complete the bird migration puzzle.